1. Predicting paravalvular leak after transcatheter mitral valve replacement using commercially available software modeling
- Author
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Ashish Pershad, Kapildeo Lotun, Abhishek C. Sawant, Alejandro Pena, Timothy Byrne, Aneesh Kalya, Michael F. Morris, and H. Kenith Fang
- Subjects
Male ,Patient-Specific Modeling ,Cardiac Catheterization ,medicine.medical_specialty ,Computed Tomography Angiography ,medicine.medical_treatment ,Computed tomography ,030204 cardiovascular system & hematology ,Coronary Angiography ,Risk Assessment ,Severity of Illness Index ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,Predictive Value of Tests ,Risk Factors ,Internal medicine ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,cardiovascular diseases ,Mitral annulus ,Paravalvular leak ,Aged ,Retrospective Studies ,Computed tomography angiography ,Aged, 80 and over ,Heart Valve Prosthesis Implantation ,Univariate analysis ,Mitral regurgitation ,medicine.diagnostic_test ,business.industry ,Arizona ,Mitral valve replacement ,Mitral Valve Insufficiency ,Middle Aged ,Predictive value ,Treatment Outcome ,Cardiology ,Mitral Valve ,Female ,Cardiology and Cardiovascular Medicine ,business ,Software - Abstract
There is limited data identifying patients at risk for significant mitral regurgitation (MR) after transcatheter mitral valve replacement (TMVR). We hypothesized that software modeling based on computed tomography angiography (CTA) can predict the risk of moderate or severe MR after TMVR.58 consecutive patients underwent TMVR at two institutions, including 31 valve-in-valve, 16 valve-in-ring, and 11 valve-in-mitral annular calcification. 12 (20%) patients developed moderate or severe MR due to paravalvular leak (PVL).The software model correctly predicted 8 (67%) patients with significant PVL, resulting in sensitivity of 67%, specificity 96%, positive predictive value 89%, and negative predictive value 86%. There was excellent agreement between CTA readers using software modeling to predict PVL (kappa 0.92; p 0.01). On univariate analysis, CTA predictors of moderate or severe PVL included presence of a gap between the virtual valve and mitral annulus on the software model (OR 48; p 0.01), mitral annular area (OR 1.02; p 0.01), and % valve oversizing (OR 0.9; p 0.01). On multivariate analysis, only presence of a gap on the software model remained significant (OR 36.8; p 0.01).Software modeling using pre-procedural CTA is a straightforward method for predicting the risk of moderate and severe MR due to PVL after TMVR.
- Published
- 2020
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